SEIF: Augmented Symbolic Execution for Information Flow Verification

We present SEIF, an exploratory methodology for information flow verification based on symbolic execution. SEIF begins with a statically built overapproximation of the information flow through a design and uses guided symbolic execution to provide a more precise picture of how information flows from a given set of security critical signals. SEIF can recognize and eliminate non-flows with high precision and for the true flows can find the corresponding paths through the design state with high coverage. We evaluate SEIF on two open-source CPUs, an AES core, and the AKER access control module. SEIF can be used to find counterexamples to information flow properties, and also to explore all flows originating from a source signal of interest. SEIF accounts for 86-90% of statically identified possible flows in three open-source designs. SEIF's search strategies enable exploring the designs for 10-12 clock cycles in 4-6 seconds on average, demonstrating that this new exploratory style of information flow analysis can be practical.